The present invention generally relates to ultrasound. In particular, the present invention relates to data dependent color wall filters used in imaging devices or systems for performing diagnostic ultrasound imaging.
Known methods of performing diagnostic ultrasound imaging include B- and M-modes (used to image internal, physical structure), Doppler mode, and color flow mode. The color flow mode is primarily used to image flow characteristics, such as flow characteristics in blood vessels for example. Ultrasound color flow mode is typically used to detect the velocity of blood flow toward/away from an ultrasound transducer. Ultrasound color flow mode utilizes similar techniques used in Doppler mode. Whereas the Doppler mode displays velocity versus time for a single selected sample volume, ultrasound color flow mode displays hundreds of adjacent sample volumes simultaneously. The adjacent sample volumes are laid over a B-mode image and color-coded to represent each sample volume's velocity.
Using Doppler mode effects to measure blood flow in the heart and vessels is known. The amplitude of the reflected waves may be employed to produce black and white images of the tissues, while the frequency shift of backscattered waves may be used to measure the velocity of the backscatterer from tissue or blood. The change or shift in backscattered frequency increases when blood flows toward the ultrasound transducer and decreases when blood flows away from the ultrasound transducer. Color flow images may be produced by superimposing a color image of the velocity of the moving material, blood for example, over the black and white anatomical image. The measured velocity of flow at each pixel determines its color.
It is contemplated that the blood may contain at least one of blood, stationary or slow moving materials and moving materials. One limitation associated with taking Doppler effect measurements of reflected ultrasound waves from blood is that the received echo signal typically contains a large component produced by the stationary or slow moving tissues (alternatively referred to as “clutter” and “color flash artifacts” respectively), whereas the blood reflects ultrasound waves very weakly. The stationary tissues in the blood do not produce any frequency shift in the reflected waves. Therefore these components may be easily filtered out (alternatively referred to as “clutter suppression”) without affecting the flow measurement. However, the reflections produced by moving tissue due to cardiac or respiratory motion are frequency shifted and may completely overwhelm signals from the slowly flowing blood.
In standard color flow processing, a high pass filter (alternatively referred to as a “wall filter”) may be applied to the data before a color flow estimate is made. This filter is adapted to remove signal components produced by tissue surrounding the blood flow of interest. If these signal components are not removed, the resulting velocity estimate may include a combination of the velocities from the blood flow and the surrounding tissue. The backscatter component from tissue is many times greater than that produced by the blood component, so the velocity estimate will most likely be more representative of the tissue, rather than the blood flow. In order to get the flow velocity, the tissue signal must be filtered out.
When a high-flow-velocity area (a blood vessel for example) is imaged in color flow mode, the region of high amplitude centered around the zero frequency represents the presence of some fairly non-moving structure (a blood vessel wall for example), while the region of somewhat less amplitude centered around some relatively high frequency represents the presence of high flow velocity (blood flow for example). Because of the large difference in frequency between the non-moving structure and the fast-moving blood flow, a wall filter may be used to eliminate a portion of the frequency response corresponding to the non-moving wall has been eliminated. After such wall filtering, some scheme for determining the maximum remaining amplitude (i.e., the amplitude of the high-velocity blood flow) may be utilized so that the flow velocity for that particular sample volume may be displayed.
However, a problem may arise in applying wall filtering in low-flow-velocity imaging. Since the frequencies of the non-moving wall and the slow-moving flow are close together, it is difficult to effectively apply a wall filter to eliminate the “wall” response without resulting in a distorted slow-flow response portion (see FIG. 2B).
Known color flow processors assume that the large signal returning from the surrounding tissue is static (i.e., the tissue is not moving). If such assumption is true, the in-phase and quadrature I and Q data may be filtered separately using simple real filters which remove the DC component and the very low frequencies. The cutoff frequency of these high pass filters may be varied for a given application by changing the filter coefficients.
The assumption with respect to static tissue is generally valid for radiology applications, except in the abdomen, where residual respiratory and cardiac motion cause some amount of tissue motion. In addition, the motion of the handheld transducer approximates or looks like tissue motion. Since the velocity of this motion is usually slow compared to the velocity of the blood flow being imaged, the operator may set the wall filter cutoff frequency high enough to filter out the tissue signal component. Filtering in this way, however, may also remove signals from low-velocity blood flow, often the very signals that the operator wants to image.
Some prior art systems use a wall filter that is manually adjusted by the operator to filter out a narrow band of frequencies in the echo signal centered on the carrier frequency where static signals lie. The bandwidth is adjusted so that the reflected signals from the slow moving wall are eliminated without distorting the measurement of blood flow. If the filter bandwidth is set too wide, signals from slowly moving blood may be eliminated. It should be appreciated that this filter setting is static and is applied over the whole image. As a result, the filter may work adequately at some locations in the field of view of the image, but not at other locations.
One processing approach described in U.S. patent application Ser. No. 08/001,998, incorporated herein by reference in its entirety, uses adaptive wall filtering. Such adaptive wall filtering mixes the wall signal down to zero frequency, then removes the wall signal using a real time domain filter, to filter the I data and the Q data. This reduces the amplitude of the wall signal and enables the flow signal to be detected with greater accuracy, and at lower velocities than previous known processes that don't use this approach. The adaptive wall filter automatically adjusts its center frequency and bandwidth as a function of the received echo signal. A complex mixer receives the received echo signal and outputs a modified echo signal which is shifted in frequency by an amount equal and opposite to the mean frequency of the received echo signal. The wall filter receives the modified echo signal and filters out a band of frequencies that are determined by the variance of the received echo signal. By shifting the frequency of the received echo signal by an amount opposite to its measured mean frequency, the signal components therein due to slowly moving tissue are effectively shifted to the center of the filter. By automatically controlling the width of the stop band of the filter in dependence on the measured variance, the signal components produced by slowly moving tissue are filtered out. The filter output is then processed in a conventional manner to produce a color signal indicative of flow velocity.
Known processing approaches comprise separately reducing flash and suppressing clutter as described in commonly assigned U.S. Pat. No. 5,524,629, which is incorporated herein by reference in its entirety. This approach uses a complex rotation of the input data, so that the motion is placed at DC (OHz). This approach assumes a high pass wall filter will filter out the slow motion tissue. It should be appreciated that the wall filters may have very low cutoff frequencies. Therefore, the complex rotations may not insure that the output of the first stage or module of the bi-quad filter is close to zero.